class_docstr: Feature fusion block.
docstr: Forward pass.
  
  Returns:
      tensor: output
docstr_tok: ["Forward","pass",".","Returns",":","tensor",":","output"]
code: def forward(self, *xs):
      """Forward pass.
  
      Returns:
          tensor: output
      """
      output = xs[0]
  
      if len(xs) == 2:
          res = self.resConfUnit1(xs[1])
          output = self.skip_add.add(output, res)
          # output += res
  
      output = self.resConfUnit2(output)
  
      output = nn.functional.interpolate(
          output,
          scale_factor=2,
          mode="bilinear",
          align_corners=self.align_corners,
      )
  
      output = self.out_conv(output)
  
      return output
  
imports: import torch
  import torch.nn
  from .vit import _make_pretrained_vitb_rn50_384, _make_pretrained_vitl16_384, _make_pretrained_vitb16_384, forward_vit
label_desc: Use image node_id 2 for calling the FeatureFusionBlock_custom obj's underlying member method code with example usage: obj.forward() and returns: output